Technologies
This technology is a database of annotated genes involved in hair follicle biology that enables the identification of key gene-phenotype relationships in hair disorders.
Advances in genome sequencing have enabled large databases that detail gene-disease relationships but fail to fully integrate information preventing us from understanding how genes act together participating in pathways and how pathways interact with each other to maintain tissue homeostasis and prevent disease. Such knowledge would allow us to identify and prioritize biological points of intervention for therapeutic development and may reveal rationale for drug repurposing. For dermatological diseases such as hair disorders, hundreds of genes have been identified for which a single mutation is sufficient to generate disease. However, these genes have yet to be subject to comprehensive analysis. As such, there is a need for a method that assembles and annotates genes associated with hair disorders to identify key gene-phenotype relationships for improved diagnosis and treatment.
This technology is a database of annotated genes involved in hair follicle biology that enables the identification of relationships among genetic drivers of disease. Using an unsupervised hierarchical algorithm, a database of nearly 700 genes with single mutations associated with observable disease phenotypes were organized into 35 gene clusters. This strategy also uses an annotation enrichment analysis to provide high-resolution characterization of relevant physiological processes. By providing a large database of genes involved in hair disorders and clustering them into biological modules, this technology may be used to identify key gene-phenotype relationships for improved diagnosis and treatment of hair disorders.
This technology was used to identify previously unknown genetic contributions from Hippo signaling to hair disorders.
IR CU18023
Licensing Contact: Joan Martinez